Are the renewables affecting the income distribution and ... · al. 2011, 2012, Econ Anal Policy; Frondel et al. 2014, 2015, Econ Anal Policy). Vienna, 6th September 2017. Motivation

UNIVERSITY OF BEIRA INTERIOR

Covilhã | Portugal

15th IAEE European Conference 2017Heading towards sustainable energy systems:

Evolution or Revolution?Vienna, 6th September 2017

Diogo André Pereira, António Cardoso Marques, José Alberto FuinhasPresenter contacts: [email protected];

[email protected]

Are the renewables affecting the income distribution and the risk of poverty of households?


Covilhã | Portugal

2


Evolution or Revolution?Pereira, Marques, and Fuinhas

Agenda

Motivation What is already known; Research questions;

Methodology Data assess; Methodology used;

Results The implications of income distribution on the RES deployment; The consequences of RES deployment on the income distribution; The effects of RES implementation on the households risk of poverty;

Conclusions

Possible solutions to mitigate the negative effects on society

Vienna, 6th September 2017

Motivation

Methodology

Results

Conclusions


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Motivation

The installed capacity of RES have been deployed in high amounts: But, the incomes of households are significant to explain this high implementation?

The intermittent RES have been deployed mainly by fiscal and financial policies: Who have payed the cost of this promotion schemes? Who have benefiting with this policy-driven guidance?

The RES capacities have been deployed at a fast tendency, but the electricity price as increasing likewise: How poor households have been leading with this increasing electricity prices?

So, one must understand the impacts of RES implementation on both income distribution, and on the risk of poverty or social exclusion of households.

How should the policy design develop to safeguard the poor households?


Motivation

Methodology

Results

Conclusions


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What is already Known

Public Policies Supporting Renewables and CO2 emissions are drivers of RESdeployment (e.g. Marques et al., 2010, JEPO; Aguirre and Ibikunle, 2014, JEPO; Polzinet al. 2015, JEPO);

RES are restricting the announced benefits, and the fossil fuels installed capacity have been required, and put into standby (e.g. Al-Mulali et al., 2014, RSER; Dogan, 2015, RSER; Green and Vasilakos, 2010, JEPO; Marques and Fuinhas, 2016, RSE);

The feed-in tariffs have been an attractive instrument do deploy large amounts of solar PV and wind power (e.g. Marques et al., 2010, JEPO; Polzin et al. 2015, JEPO; Frondel et al. 2015, Econ Anal Policy);

Increasing electricity prices have regressive impacts on poor households (Nelson et al. 2011, 2012, Econ Anal Policy; Frondel et al. 2014, 2015, Econ Anal Policy).


Motivation

Methodology

Results

Conclusions


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Research questions

The income of social classes have been driven RES promotion?

What have been the consequences of RES deployment onincome distribution?

The RES implementation have been increasing the risk ofpoverty and social exclusion?


Motivation

Methodology

Results

Conclusions


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Data

Countries under analysis: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden and United Kingdom.

Explained / Explaining variables:• Installed capacity of all RES;• Electricity generation from all RES;• Installed capacity of wind power;• Electricity generation from wind power;• Installed capacity of solar PV;• Electricity generation from Solar PV;• Installed capacity of hydro power;• Electricity generation from hydro power;• Percentage of household’s mean disposable

income in relation to the total mean disposable income;

• Number of peoples, in households groups, at risk of poverty and social exclusion.

Households groups/types:• Single person;• Single person with dependent children;• Two adults;• Two adults younger than 65 years;• Two adults, at least one aged 65 years or over;• Two adults with one dependent children;• Two adults with two dependent children;• Two adults with three or more dependent children;• Two adults or more without dependent children;• Two or more adults with dependent children;• Three or more adults;• Three or more adults with dependent children;• All households without dependent children;• All households with dependent children.


Motivation

Methodology

Results

Conclusions


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Econometric procedures

Cross-section dependence and unit roots tests

CD-test (Pesaran, 2004); 2nd generation CIPS unit root test (Pesaran, 2007)

Correlation matrix and variance inflation factors

Kao’s residual cointegration test

Model Specification tests

Heteroskedasticity, serial correlation, contemporaneous correlation; and Fixed Effects vs. Random Effects

Autoregressive Distributed Lag (ARDL) model

Breakdown of the total effects into both short-run (semi-elasticities) and long-run (elasticities) effects


Motivation

Methodology

Results

Conclusions


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In short:

Cross-section dependence

Strongly supported the presence of cross-section in almost of variables.

Unit roots Second generation unit roots test, CIPS, proves that all variables are I(1) in their levels.

ARDL modelling

Adequacy of assessing the short-rundynamics and the long-run equilibrium.

Allows variables with long memory patternsto be handled appropriately.

Specification tests

ARDL approach estimated by Driscoll-Kraay estimator with fixed effects

Cointegration The Kao residual cointegration test strongly supported the

presence of long-run relationships between series.

Driscoll Kraay (1998) estimator is a covariance matrix estimator, and their small-sample properties (case of thisresearch) are considerably better than the alternative covariance estimators, mainly when cross-sectional dependence,heteroskedasticity, autocorrelation, and contemporaneous correlation are present (Hoechle, 2007, SJ)

Presence of heteroskedasticity, first order autocorrelation, and panel fixed effects.


Motivation

Methodology

Results

Conclusions


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Results (RES models)

Key point:

The velocity of adjustment of RES models are slow, except on hydro

power models

The Natural gas consumption and the electricity prices has been drive the RES implementation, except wind

power;

Almost of the households has been stimulated the hydro power

deployment;

The households with two or more adults have been driven the solar PV

deployment.

Moldels RES_IC RES_GEN HYDRO_IC HYDRO_GEN WIND_IC WIND_GEN SOL_IC SOL_GEN

Single person (LR) -** (LR) -** (LR) +**(SR) -*(LR) -***

(LR) -***(SR) -***(LR) -***

(LR) -***

Single person with dependent children

(LR) -** (LR) +*** (SR) +** (LR) -*** (SR) +**(SR) -**(LR) -***

Two adults younger than 65 years (SR) -* (SR) +* (LR) -*** (LR) -** (SR) -**

Two adults, at least one aged 65 years or over

(LR) -* (LR) +***

Two adults with one dependent child

(SR) -***(LR) -*

(LR) -*** (LR) +**(SR) -***(LR) -***

(SR) -***(LR) -***

(SR) -***(LR) -***

(SR) -***(LR) -***

Two adults with two dependent children

(LR) +** (LR) +** (LR) +***

Two adults with three or more dependent children

(LR) -**(SR) -***(LR) -***

(SR) -***(LR) -***

(LR) -** (LR) +**

Three or more adults (LR) +* (LR) -*** (LR) +**

Three or more adults with dependent children

(SR) -***(LR) -*

(SR) +**(SR) -**(LR) -***

Natural gas consumption (SR) +*** (SR) +*** (LR) +*** (SR) +*** (SR) -***(SR) -**(LR) -**

(LR) +***

Electricity price (LR) +*** (LR) +*** (LR) +*** (LR) +** (SR) -*(SR) +**(LR) +***

Greenhouse gases intensity (SR) -*** (SR) -***(SR) -**(LR) -***

(SR) -***(LR) -***

(LR) -***

Energy intensity(SR) -***(LR) -***

(LR) +*** (SR) -**(SR) -**(LR) -***

Gross Domestic Product (LR) -*** (LR) -*** (LR) +*** (SR) -*(SR) -**(LR) -***

Public expenses on education(SR) -***(LR) -***

(LR) -* (LR) -*** (SR) -**(SR) -**(LR) -**

People living with very low work intensity

(LR) -* (SR) +*(SR) -**(LR) -***

Error Correction Mechanism -0.0728** -0.1913*** -0.5133*** -0.9567*** -0.2050*** -0.2355*** -0.1402*** -0.2204***


Motivation

Methodology

Results

Conclusions


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Results (income models)

Negative

• Single person with dependent children• Two adults• Two adults, at least one aged 65 years or over• Two adults with one dependent children• Two adults with two dependent children• Two or more adults with dependent children• Three or more adults• Households with dependent children

Positive

• Households without dependent children

• Single Person

Negative Positive

Two or more adults without dependent

children

Two adults, at least one aged 65 years

or over

Two adults younger than 65 years

Three or more adults

Two adults with one dependent

children

Single person

Wind Power installed capacity


Motivation

Methodology

Results

Conclusions


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11




Negative Positive

Two adults, at least one aged 65 years or

over

Single person with dependent children

Single person


Two adults with three or more

dependent children

Two adults younger than 65 years

Negative Positive

Hydro Power installed capacity


Motivation

Methodology

Results

Conclusions


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Hydro Power installed capacity

Negative

• Single person with dependent children

• Two adults with one dependent children

• Two adults with two dependent children

• Two adults with three or more dependent children

• Two or more adults with dependent children

• Households with dependent children

Positive

• Two or more adults without dependent children

• Three or more adults

• households without dependent children

Negative

• Two adults with three dependent children

• Two or more adults without dependent children

• Three or more adults

• Households without dependent children

Positive

• Single person• Two adults with one dependent

children• Two adults with two dependent

children• Two or more adults with dependent

children• Households with dependent children


Motivation

Methodology

Results

Conclusions


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Results (risk models)

Decrease Increase Decrease Increase

Energy

Natural gas consumption

Solar PV

Greenhouse gas emissions

Electricity Price

Hydro power

Single Person with dependent children

Decrease Increase

Decrease Increase Decrease Increase Decrease Increase

Solar PV

Hydro power


Wind power

Two adults with one children


Motivation

Methodology

Results

Conclusions


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Decrease Increase

Decrease Increase Decrease Increase

Electricity price

RES generation

Hydro power


Solar PV

Wind Power

Decrease Increase

Three or more adults with children

Decrease Increase

Greenhouse gas

emissions


Two or more adults without children

Decrease Increase


RES generation

Hydro power

Energy


Electricity price

Two or more adults with children


Motivation

Methodology

Results

Conclusions


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Conclusion

The electricity price has stimulated the RES, which discloses that they are ready to operate at market prices, and to compete with fossil fuels;

The income of households not have been stimulating the wind power, this emphasizes that these high investments should continue to be financed through public policies;

The solar PV has decreased the income of households, consequently, it increases their risk of poverty and social exclusion;

The hydro power installed capacity has been effective to reduce the risk of poverty of households.

The public energy policies should be focused to help households to save electricity, in order to reduce their electricity cost burden. Consequently, helping them support the

costs of energy transition.


Motivation

Methodology

Results

Conclusions


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Possible solutions to mitigate the effects

Integrating renewables is not only about building new wind farms or PV power plants;

Besides, integrating RES is not give dispatch priority, it is need match the electricity demand with the availability of natural resources.

To decrease the impact on income distribution, the economy ought to be prepared for (instance):

Promoting the energy conservation;

Subsiding energy efficiency home appliances, instead RES deployment;

Rewarding change of consumption routines, for instance through electricity tariffs;

Distribute the cost of RES deployment by taxations, instead by electricity price;

Promoting further generation of their own electricity.



Covilhã | Portugal


Evolution or Revolution?

Diogo André Pereira, António Cardoso Marques, José Alberto FuinhasPresenter contacts: [email protected];

[email protected]

Are the renewable energies affecting the income

distribution and the risk of poverty of households?


Motivation

Methodology

Results

Conclusions


Covilhã | Portugal

18


Evolution or Revolution?Pereira, Marques, and Fuinhas Austria, 6th September 2017


ModelsINC

Single person

Single person

with dependent

children

Two adults

Two adults younger than 65

years


over

Two adults with one

dependent child

Two adults with two

dependent children

Two adults with three

or more dependent

children

Two or more adults

without dependent

children

Two or more

adults with dependent

children


Three or more


children

Households without

dependent children

Households with

dependent children

Low work(SR) -***(LR) -**

(SR) -***(LR) -*** (LR) -***

(SR) -***(LR) -***

(SR) -***(LR) -*** (SR) +*** (SR) -**

(SR) -**(LR) -*** -

HYDRO_IC (SR) +*** (SR) +***(SR) -*(LR) -* (SR) +*** (SR) -*** (SR) -*** -

WIND_IC (LR) -*** (LR) +* (LR) +***(SR) -***(LR) -*** (LR) +*** (SR) -*** -

SOL_IC(SR) -**(LR) +***

(SR) -**(LR) -*** (SR) -** (SR) -**

(SR) -**(LR) -*** (LR) -*** (LR) -* (LR) -*** - (LR) +** (LR) -***

RES_GEN (LR) -*** (LR) +*** (LR) +** (LR) -***(SR) +***(LR) +*** -

GASCONS (SR) -***(SR) -***(LR) -*** (LR) -*** (LR) -*** (LR) -*** (LR) +** (LR) -*** (LR) +*** - (LR) +*** (LR) -***

PRICE_ELE (SR) +** (LR) +***(SR) +***(LR) +** (SR) -*

(SR) -***(LR) -**

(SR) +**(LR) +**

(SR) -***(LR) -*** -

(SR) -***(LR) -***

(SR) +***(LR) +***

GEH_INTS (LR) -*** (LR) -** (LR) -**(SR) +*(LR) +*** (SR) -** (LR) +*** (SR) -* - (SR) -**

ENERG_INTS (SR) +*** (LR) -** (LR) -*** (LR) +*** (LR) -*** (SR) -**

(SR) -**(LR) -*** -

GDP (LR) -*** (LR) -*** (SR) -***(SR) -*(LR) +***

(SR) -***(LR) -*** (LR) -***

(SR) -**(LR) -*** (LR) +*** (SR) -***

(SR) +**(LR) +*** (SR) -** - (SR) -* (SR) +**

EDU_EXPS(SR) -***(LR) -*** (SR) -*** (SR) -** (SR) -*** (SR) -*

(SR) +**(LR) +*** (SR) +*** (SR) -*

(SR) +***(LR) +*** (SR) +** -

(SR) -***(LR) -***

(SR) +***(LR) +***

ECM -0.6545*** -0.7246*** -0.5196*** -0.6323*** -0.6213*** -0.8272*** -0.7082*** -0.8544*** -0.6167*** -0.6361*** -0.8724*** - -0.5918*** -0.5853***

The RES deployment have a negative impact on the income distribution, benefiting the wealthy households, and harmingthe low-income households. Low-income households have been threatened by energy poverty.

Motivation

Methodology

Results

Conclusions


Covilhã | Portugal

19


Evolution or Revolution?Pereira, Marques, and Fuinhas Austria, 6th September 2017


ModelsRISK

Single person

Single person

with dependent

children

Two adults

Two adults younger than 65

years


over

Two adults with one

dependent child

Two adults with two

dependent children

Two adults with three

or more dependent

children

Two or more adults

without dependent

children

Two or more


children


Three or more


children

Households without

dependent children

Households with

dependent children

Low work (SR) +***(SR) +***(LR) +***

(SR) +***(LR) +***

(SR) +***(LR) +*** (SR) +***

(SR) +***(LR) +***

(SR) +***(LR) +*** -

(SR) +***(LR) +***

(SR) +***(LR) +***

(SR) +***(LR) +*** (SR) +***

(SR) +***(LR) +***

(SR) +***(LR) +***

HYDRO_IC (SR) -* (SR) -*** (LR) -*** (LR) +** (SR) +** - (SR) +*** (LR) -***(SR) +**(LR) +*** (SR) +***

WIND_IC (LR) -**(SR) +*(LR) -***

(SR) +**(LR) -*** -

(SR) +*(LR) +*** (SR) -**

SOL_IC (SR) +**(SR) +***(LR) +***

(SR) +**(LR) +*** (SR) -***

(SR) +*(LR) +*** (LR) +*** - (LR) -*** (LR) +**

RES_GEN (LR) -*** (SR) +*(SR) -**(LR) -*** - (LR) +***

(SR) -**(LR) -***

(SR) +**(LR) +*** (LR) -***

GASCONS (SR) +**(SR) +***(LR) +*** (LR) -***

(SR) -*(LR) -*** (LR) -*** (SR) -*** (LR) +*** - (LR) -** (LR) +*** (LR) -***

PRICE_ELE (LR) -*** (LR) -*** - (LR) -*** (LR) +*** (SR) +** (LR) -*

GEH_INTS (LR) +**(SR) -***(LR) -** (LR) +*** (SR) -** (LR) +***

(SR) -**(LR) +** - (LR) +*** (SR) -*** (LR) -**

(SR) +*(LR) +***

(SR) -***(LR) -***

ENERG_INTS

(SR) -***(LR) -*** (LR) +*** (SR) -** (LR) -*** (SR) -*** (SR) +* - (LR) -*** (SR) -***

GDP (LR) +*** (LR) -*** (SR) -** (SR) +** - (LR) -***(SR) -**(LR) -***

EDU_EXPS(SR) +***(LR) +*** (LR) -*** (LR) -***

(SR) +**(LR) +*** (SR) +* -

ECM -0.4812*** -0.9335*** -0.5869*** -0.7926*** -0.4255*** -0.8610*** -0.9840*** - -0.6345*** -0.8380*** -0.9431*** -0.8745*** -0.4831*** -0.8514***

The ECM values reveals the presence of long memory in the data, further, all are stable and able to return to the equilibrium path after a disturbance.

Documents

Are the renewables affecting the income distribution and ... · al. 2011, 2012, Econ Anal Policy; Frondel et al. 2014, 2015, Econ Anal Policy). Vienna, 6th September 2017. Motivation